This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1328) Decision Support for Health Professionals (1137)

Published on in Vol 21, No 7 (2019): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14286, first published .
A Novel Intelligent Scan Assistant System for Early Pregnancy Diagnosis by Ultrasound: Clinical Decision Support System Evaluation Study

A Novel Intelligent Scan Assistant System for Early Pregnancy Diagnosis by Ultrasound: Clinical Decision Support System Evaluation Study

A Novel Intelligent Scan Assistant System for Early Pregnancy Diagnosis by Ultrasound: Clinical Decision Support System Evaluation Study

Authors of this article:

Ferdinand Dhombres1, 2 Author Orcid Image ;   Paul Maurice1, 2 Author Orcid Image ;   Lucie Guilbaud1 Author Orcid Image ;   Loriane Franchinard1 Author Orcid Image ;   Barbara Dias1 Author Orcid Image ;   Jean Charlet2, 3 Author Orcid Image ;   Eléonore Blondiaux4 Author Orcid Image ;   Babak Khoshnood5 Author Orcid Image ;   Davor Jurkovic6 Author Orcid Image ;   Eric Jauniaux6 Author Orcid Image ;   Jean-Marie Jouannic1, 2 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Journals

  1. Tao L, Zhang C, Zeng L, Zhu S, Li N, Li W, Zhang H, Zhao Y, Zhan S, Ji H. Accuracy and Effects of Clinical Decision Support Systems Integrated With BMJ Best Practice–Aided Diagnosis: Interrupted Time Series Study. JMIR Medical Informatics 2020;8(1):e16912 View
  2. Owais M, Arsalan M, Mahmood T, Kang J, Park K. Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation. Journal of Medical Internet Research 2020;22(11):e18563 View
  3. Chen Z, Liu Z, Du M, Wang Z. Artificial Intelligence in Obstetric Ultrasound: An Update and Future Applications. Frontiers in Medicine 2021;8 View
  4. Dhombres F, Bonnard J, Bailly K, Maurice P, Papageorghiou A, Jouannic J. Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review. Journal of Medical Internet Research 2022;24(4):e35465 View
  5. Douer N, Meyer J. Theoretical, Measured, and Subjective Responsibility in Aided Decision Making. ACM Transactions on Interactive Intelligent Systems 2021;11(1):1 View
  6. Dhombres F, Morgan P, Chaudhari B, Filges I, Sparks T, Lapunzina P, Roscioli T, Agarwal U, Aggarwal S, Beneteau C, Cacheiro P, Carmody L, Collardeau‐Frachon S, Dempsey E, Dufke A, Duyzend M, el Ghosh M, Giordano J, Glad R, Grinfelde I, Iliescu D, Ladewig M, Munoz‐Torres M, Pollazzon M, Radio F, Rodo C, Silva R, Smedley D, Sundaramurthi J, Toro S, Valenzuela I, Vasilevsky N, Wapner R, Zemet R, Haendel M, Robinson P. Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology. American Journal of Medical Genetics Part C: Seminars in Medical Genetics 2022;190(2):231 View
  7. Nuutinen M, Leskelä R. Systematic Review of the Performance Evaluation of Clinicians with or without the Aid of Clinical Decision Support System. SSRN Electronic Journal 2023 View
  8. Nuutinen M, Leskelä R. Systematic review of the performance evaluation of clinicians with or without the aid of machine learning clinical decision support system. Health and Technology 2023;13(4):557 View
  9. Gargano M, Matentzoglu N, Coleman B, Addo-Lartey E, Anagnostopoulos A, Anderton J, Avillach P, Bagley A, Bakštein E, Balhoff J, Baynam G, Bello S, Berk M, Bertram H, Bishop S, Blau H, Bodenstein D, Botas P, Boztug K, Čady J, Callahan T, Cameron R, Carbon S, Castellanos F, Caufield J, Chan L, Chute C, Cruz-Rojo J, Dahan-Oliel N, Davids J, de Dieuleveult M, de Souza V, de Vries B, de Vries E, DePaulo J, Derfalvi B, Dhombres F, Diaz-Byrd C, Dingemans A, Donadille B, Duyzend M, Elfeky R, Essaid S, Fabrizzi C, Fico G, Firth H, Freudenberg-Hua Y, Fullerton J, Gabriel D, Gilmour K, Giordano J, Goes F, Moses R, Green I, Griese M, Groza T, Gu W, Guthrie J, Gyori B, Hamosh A, Hanauer M, Hanušová K, He Y, Hegde H, Helbig I, Holasová K, Hoyt C, Huang S, Hurwitz E, Jacobsen J, Jiang X, Joseph L, Keramatian K, King B, Knoflach K, Koolen D, Kraus M, Kroll C, Kusters M, Ladewig M, Lagorce D, Lai M, Lapunzina P, Laraway B, Lewis-Smith D, Li X, Lucano C, Majd M, Marazita M, Martinez-Glez V, McHenry T, McInnis M, McMurry J, Mihulová M, Millett C, Mitchell P, Moslerová V, Narutomi K, Nematollahi S, Nevado J, Nierenberg A, Čajbiková N, Nurnberger J, Ogishima S, Olson D, Ortiz A, Pachajoa H, Perez de Nanclares G, Peters A, Putman T, Rapp C, Rath A, Reese J, Rekerle L, Roberts A, Roy S, Sanders S, Schuetz C, Schulte E, Schulze T, Schwarz M, Scott K, Seelow D, Seitz B, Shen Y, Similuk M, Simon E, Singh B, Smedley D, Smith C, Smolinsky J, Sperry S, Stafford E, Stefancsik R, Steinhaus R, Strawbridge R, Sundaramurthi J, Talapova P, Tenorio Castano J, Tesner P, Thomas R, Thurm A, Turnovec M, van Gijn M, Vasilevsky N, Vlčková M, Walden A, Wang K, Wapner R, Ware J, Wiafe A, Wiafe S, Wiggins L, Williams A, Wu C, Wyrwoll M, Xiong H, Yalin N, Yamamoto Y, Yatham L, Yocum A, Young A, Yüksel Z, Zandi P, Zankl A, Zarante I, Zvolský M, Toro S, Carmody L, Harris N, Munoz-Torres M, Danis D, Mungall C, Köhler S, Haendel M, Robinson P. The Human Phenotype Ontology in 2024: phenotypes around the world. Nucleic Acids Research 2024;52(D1):D1333 View

Books/Policy Documents

  1. Verma S, Singh A, Dobhal K, Gairola N, Jakhmola V. Artificial Intelligence and Machine Learning for Women’s Health Issues. View